A Novel Method to Improve Quality Surface Coverage in Multi-View Capture A Novel Method to Improve Quality Surface Coverage in Multi-View Capture wei-lun huang, davood tashayyod, amir gandjbakhche, michael kazhdan, mehran armand September 9, 2025 The depth of field of a camera is a limiting factor for applications that require taking images at a short subject-to-camera distance or using a large focal length, such as total body photography, archaeology, and other close-range photogrammetry applications. Furthermore, in multi-view capture, where the target is larger than the camera’s field of view, an efficient way to optimize surface coverage captured with quality remains a challenge. Given the 3D mesh of the target object and camera poses, we propose a novel method to derive a focus distance for each camera that optimizes the quality of the covered surface area. We first design an Expectation-Minimization (EM) algorithm to assign points on the mesh uniquely to cameras and then solve for a focus distance for each camera given the associated point set. We further improve the quality surface coverage by proposing a -view algorithm that solves for the points assignment and focus distances by considering multiple views simultaneously. We demonstrate the effectiveness of the proposed method under various simulations for total body photography. The EM and -view algorithms improve the relative cost of the baseline single-view methods by at least 24% and 28% respectively, corresponding to increasing the in-focus surface area by roughly 1550cm2 and 1780cm2. We believe the algorithms can be useful in a number of vision applications that require photogrammetric details but are limited by the depth of field. Published In : arXiv​ Latest Publications All Posts Publication A Novel Method to Improve Quality Surface Coverage in Multi-View Capture September 9, 2025Lumo Scan A Shape-Aware Total Body Photography System for In-focus Surface Coverage Optimization September 9, 2025Lumo Scan Ready to Experience the Future of Scanning?

A Shape-Aware Total Body Photography System for In-focus Surface Coverage Optimization A Shape-Aware Total Body Photography System for In-focus Surface Coverage Optimization wei-lun huang, joshua liu, davood tashayyod, jun kang, amir gandjbakhcke, misha kazhdan, mehran armand September 9, 2025 Total Body Photography (TBP) is becoming a useful screening tool for patients at high risk for skin cancer. While much progress has been made, existing TBP systems can be further improved for automatic detection and analysis of suspicious skin lesions, which is in part related to the resolution and sharpness of acquired images. This paper proposes a novel shape-aware TBP system automatically capturing full-body images while optimizing image quality in terms of resolution and sharpness over the body surface. The system uses depth and RGB cameras mounted on a 360-degree rotary beam, along with 3D body shape estimation and an in-focus surface optimization method to select the optimal focus distance for each camera pose. This allows for optimizing the focused coverage over the complex 3D geometry of the human body given the calibrated camera poses. We evaluate the effectiveness of the system in capturing high-fidelity body images. The proposed system achieves an average resolution of 0.068 mm/pixel and 0.0566 mm/pixel with approximately 85% and 95% of surface area in-focus, evaluated on simulation data of diverse body shapes and poses as well as a real scan of a mannequin respectively. Furthermore, the proposed shape-aware focus method outperforms existing focus protocols (e.g. auto-focus). We believe the high-fidelity imaging enabled by the proposed system will improve automated skin lesion analysis for skin cancer screening. Published In : IEEE Journal of Biomedical and Health Informatics ( Early Access ) Latest Publications All Posts Publication A Novel Method to Improve Quality Surface Coverage in Multi-View Capture September 9, 2025Lumo Scan A Shape-Aware Total Body Photography System for In-focus Surface Coverage Optimization September 9, 2025Lumo Scan Ready to Experience the Future of Scanning?

Revisiting Lesion Tracking in 3D Total Body Photography Revisiting Lesion Tracking in 3D Total Body Photography wei-lun huang, minghao xue, zhiyou liu, davood tashayyod, jun kang, amir gandjbakhche, misha kazhdan, mehran armand September 9, 2025 Melanoma is the most deadly form of skin cancer. Tracking the evolution of nevi and detecting new lesions across the body is essential for the early detection of melanoma. Despite prior work on longitudinal tracking of skin lesions in 3D total body photography, there are still several challenges, including:1) low accuracy for finding correct lesion pairs across scans,2) sensitivity to noisy lesion detection,3) lack of large-scale datasets with numerous annotated lesion pairs. We propose a framework that takes in a pair of 3D textured meshes, matches lesions in the context of total body photography, and identifies unmatchable lesions. We start by computing correspondence maps bringing the source and target meshes to a template mesh. Using these maps to define source/target signals over the template domain, we construct a flow field aligning the mapped signals. The initial correspondence maps are then refined by advecting forward/backward along the vector field. Finally, lesion assignment is performed using the refined correspondence maps. We propose the first large-scale dataset for skin lesion tracking with 25K lesion pairs across 198 subjects. The proposed method achieves a success rate of 89.9% (at 10 mm criterion) for all pairs of annotated lesions and a matching accuracy of 98.2% for subjects with more than 200 lesions. Published In : Medical Image Analysis Informatics ( Early Access ) Latest Publications All Posts Publication A Novel Method to Improve Quality Surface Coverage in Multi-View Capture September 9, 2025Lumo Scan A Shape-Aware Total Body Photography System for In-focus Surface Coverage Optimization September 9, 2025Lumo Scan Ready to Experience the Future of Scanning?

A TBP DICOM format for total-body scanner-independent lesion evolution detection A TBP DICOM format for total-body scanner-independent lesion evolution detection minghao xue, wei-lun huang, davood tashayyod, jun kang, amir gandjbakhche, mehran armand September 9, 2025 Total-body photography (TBP) has the potential to revolutionize early detection of skin cancers by monitoring minute changes in lesions over time. However, there is no standardized Digital Imaging and Communications in Medicine (DICOM) format for TBP. In order to accommodate various TBP data types and sophisticated data preprocessing pipelines, we propose three TBP Extended Information Object Definitions (IODs) for 2D regional images, dermoscopy images, and 3D surface meshes. We introduce a comprehensive pipeline integrating advanced image processing techniques, including 3D DICOM representation, super-resolution enhancement, and style transfer for dermoscopic-like visualization. Our framework tracks individual lesions across multiple TBP scans from different imaging systems and provides cloud-based storage with a customized DICOM viewer. To demonstrate the effectiveness of our approach, we validate our framework using TBP datasets from multiple imaging systems. Our framework and proposed IODs enhance TBP interoperability and clinical utility in dermatological practice, potentially improving early skin cancer detection. Published In : SPIE Digital Library Latest Publications All Posts Publication A Novel Method to Improve Quality Surface Coverage in Multi-View Capture September 9, 2025Lumo Scan A Shape-Aware Total Body Photography System for In-focus Surface Coverage Optimization September 9, 2025Lumo Scan Ready to Experience the Future of Scanning?